1. Field of Invention
The present invention relates generally to telephony and, more particularly, to measuring the level of speech distortion in transmitted voice waveforms.
2. Discussion of the Related Art
When viewed from the perspective of the user of a telephone, the quality of a voice telephone connection depends in very large part on how the speaker""s voice on the other end of the call sounds to the listener. In particular, it is well known that users will base their assessment of the quality of each call on what might be called clarity, as determined by at least four independent characteristics:
(1) Volume of the received voice signal, which will determine whether the user will find the speech to be too loud or too soft;
(2) Noise on the line, such as static, popping, and crackle, which will determine whether the listener will have difficulty separating the speech from background noise:
(3) Echo on the line, which will determine whether speakers will be distracted by hearing their own voice echoed back to them as they are talking; and
(4) Speech distortion, caused by conditions on the telephone connection that will make the distant speaker sound xe2x80x9ctinny,xe2x80x9d or xe2x80x9craspy,xe2x80x9d or otherwise distort the voice in ways that cannot be duplicated in natural, face-to-face conversation.
Of these four characteristics, the first three have been present in telephone networks from the beginning. The fourth, speech distortion, however, has only occurred with the advent of modern digital telephone networks. The reason why this occurs in digital telephone networks is that nearly all of the possible causes of perceptible speech distortion over telephone connections stein from malfunctions in the analog-to-digital (A/D) and digital-to-analog (D/A) conversions, or in the transport of digitally encoded voice signals. Speech distortion from these sources are caused, for example, by overdriving of the A/D converter. which produces xe2x80x9cclippingxe2x80x9d of the waveform that makes speech sound mechanical, encoding that produces high levels of xe2x80x9cquantizingxe2x80x9d noise that makes speech sound xe2x80x9craspy,xe2x80x9d and malfunctions or high bit error rates in the digital transport, which results in analog waveforms at the distant end of a connection that could not possibly be produced by the human voice.
Because of the competition for customers that has emerged with the demise of the single-provider monopolies in global telephony, the quality of telephone services in general, and the question of clarity of calls, in particular, have become major concerns in marketing telephone services. Such concerns have, in turn, created ever-increasing demands for capabilities to monitor, and maintain the clarity of, telephone services to ensure that users will remain satisfied with the service they are purchasing.
Various techniques have been developed for monitoring and evaluating the factors that affect clarity of transmitted voice telephone signals. For example, techniques have been developed for refining test capabilities, establishing standards and providing models for collecting and interpreting samples of objectively measurable characteristics of telephone connections such as loss, noise, slope distortion, signal fidelity and echo path loss and delay. Further, techniques have been developed for non-intrusive monitoring which enables the collection of data from live conversation without intruding on, or illegally listening to, live telephone conversations, and thereby obtain measurements of speech power, line noise and echo path loss and delay.
Such telephone measurement techniques and technologies, together with various interpretation models have enabled the development of practices for timely detection and correction of adverse effects relating to low volume, noise and echo characteristics. Additionally, these measurement techniques have provided standards for the design of new telephone systems as well as standards for management of systems that has increased the clarity with regard to three of the clarity factors, i.e., noise, low volume and echo.
However, it would also be desirable to provide a system which is capable of processing data from live telephone conversations to measure speech distortion created in voice signals transmitted by modern digital and/or packet switched voice networks. Various techniques have been used in an attempt to measure speech distortion in digitally mastered waveforms and pseudo speech signals to predict user perception of speech distortion under various conditions. For example, a technique known as PAMS, that was developed in the United Kingdom, uses a recording of digitally mastered phonemes. According to this process, the digitally mastered phonemes are transmitted over a telephone system and recorded at the receiving end. The recorded signal is processed and compared to the originally transmitted signal to provide a measurement of the level of distortion of the transmitted signal.
Other commonly used methods of measuring distortion in audio signals have included the introduction of a sinusoidal waveform at the input of the audio signal and an analysis of the output of the audio channel to detect harmonics and other components that were not part of the original signal. This methodology, however, has certain limitations. Chief among these limitations is that the method provides no basis for assessing the user perception of speech distortion. Essentially, what this means is that there is no means for correlating what happens to individual frequencies with the overall effect of those distortions on user perception.
Further, each of these techniques are only effective when known signals are transmitted. The PAMS technique requires the transmission of a special signal containing special phonemes and a comparison of the transmitted signal with the received signal. The second technique requires transmission of sinusoidal waveforms on the audio channel. It would therefore be advantageous to provide a system that would allow measurement and interpretation of speech distortion that uses samples of natural speech from live telephone conversations and does not require the introduction of special signals or comparison with an original signal. It would also be advantageous to be able to sample such signals in a non-intrusive monitoring situation that enables collection of data from live conversations.
The present invention overcomes the disadvantages and limitations of the prior art by providing an apparatus and method that allows non-intrusive sampling of live telephone calls and processing of data from those calls to provide a measurement of the level of speech distortion of voice signals.
The present invention discloses a method of processing samples of natural speech signals to produce a measure of distortion that correlates with user perception of voice distortion. The method of processing natural speech signals is based on the creation of numerical amplitude files, representing the amplitude of the speech waveform sampled at fixed, short time intervals, and calculating therefrom consecutive differences to produce first and second discrete derivatives, which approximate the first and second continuous derivatives of the speech waveform. The present invention may therefore comprise generating a set of the discrete second derivatives from a sample of speech taken from a live telephone conversation, and analyzing the second discrete derivatives to produce the measure of distortion.
In accordance with one aspect, the present invention is directed to a method of processing samples of natural speech signals to produce a measure of distortion that correlates with user perception of voice distortion. The method comprises generating a set of discrete second derivatives of the sample and analyzing the set of discrete second derivatives to produce the measure of distortion.
In accordance with another aspect, the present invention is directed to a method of processing samples of natural speech signals to produce a measure of distortion that correlates with user perception of voice distortion. The method comprises generating a set of discrete first derivatives of the samples and analyzing the set of discrete first derivatives to produce the measure of distortion.
In accordance with another aspect, the present invention is directed to a method of calculating a measurement of a level of speech distortion in a natural speech signal. The method comprises generating a numerical amplitude data file representing the amplitude of the natural speech signal sampled at fixed, short time intervals, deriving a set of discrete second derivative data from the numerical amplitude data that approximates a second derivative of the numerical amplitude data with respect to time, and analyzing the discrete second derivative data to generate a value indicative of the likelihood a user will deem speech to be distorted.
In accordance with another aspect, the present invention is directed to a method of calculating a measurement of a level of speech distortion in a natural speech signal. The method comprises generating a numerical amplitude data file representing the amplitude of the natural speech signal sampled at fixed, short time intervals, deriving a set of discrete first derivative data from the numerical amplitude data that approximates a first derivative of the numerical amplitude data with respect to time, and analyzing the discrete first derivative data to generate a value indicative of the likelihood a user will deem speech to be distorted.
In accordance with another aspect, the present invention is directed to a method of calculating the amount of distortion of a natural speech signal. The method comprises sampling the natural voice signal to generate a sampled natural voice signal, digitizing the sampled natural voice signal to produce a digitized signal, encoding the digitized signal to produce a numerical amplitude data file, analyzing the numerical amplitude data tile to determine speech boundary points, selecting speech numerical amplitude data that is included within the speech boundary points of the numerical amplitude data file to produce a numerical speech data file, generating a set of first difference data by determining the difference between successive data points of two numerical speech data files, generating a set of second difference data by determining the difference between successive data points of the set of first difference data, statistically analyzing the first difference data and the second difference data, and generating indicators of speech distortion based on the statistical analysis of the first difference data and the second difference data.
In accordance with another aspect the present invention is directed to an apparatus for measuring distortion of an audio signal. The apparatus comprises a storage medium that stores numerically encoded representations of contiguous samples of the audio signal, and a processor that generates a set of second difference numbers that approximate a second derivative of the audio signal and that analyzes the set of second difference numbers to generate the distortion measurement.
In accordance with another aspect the present invention is directed to an apparatus for measuring distortion of an audio signal. The apparatus comprises a storage medium that stores numerically encoded representations of contiguous samples of the audio signals, and a processor that generates a set of first difference numbers that approximate a first derivative of the audio signal and that analyzes the set of first difference numbers to generate the distortion measurement.
In accordance with another aspect the present invention is directed to a system for measuring of speech distortion of voice signals transmitted over a telephone system. The system comprises a tap connected to the signal telephone that provides samples of the voice signals that are transmitted over the telephone system, a storage medium that stores numerically encoded representations of the samples, and a processor that generates a set of discrete second derivatives of the numerically encoded representations and that analyze the set of discrete second derivatives to produce the distortion measurement.
The advantages of the present invention are that it provides a way to use empirical data from actual live telephone conversations and process that data to obtain measurements of speech distortion. This analysis may be performed without the necessity of comparing the original signal with the received signal. Hence, these measurements may be made on real signals during actual telephone conversations. Additionally, the present invention may process the data, if desired, in a near real-time fashion to provide immediate measurements of speech distortion in a transmitted signal. The present invention may be used to analyze any type of audio signal to detect distortion based upon objective factors that are obtained by analyzing the signal. This may be accomplished through a non-intrusive coupling technique that collects and analyzes data samples from actual transmitted voice signals. Further, this process may be easily automated and the process complements the loss/noise/echo measurements so that an accurate measurement of overall quality may be provided that directly corresponds to user perception of quality.
Various ways of analyzing the data are disclosed including, the measurement of kurtosis of the distribution of second derivative data, the occurrence of first derivative data and second derivative data values over a predetermined threshold, the occurrence of first derivative data under a predetermined threshold, the kurtosis of the first derivative data, and any combination of these techniques. Further, any other desired techniques may be used. For example, the existence of third or fourth derivative data may further indicate the existence of unnatural sounds in the voice signal that could not have been naturally created and are the result of clipping, saturation of A/D and D/A converters, and problems with other components in the system.
The present invention is based, at least in part, on the concept that human vocal cords have a predetermined length and elasticity and accelerate within predetermined limits. Generation and analysis of various levels of derivatives of the speech signal provides a basis for detecting and determining the incidence of unnatural sounds that could not have been produced by a human voice. Further, the distribution of first discrete derivatives may be analyzed to detect clipping of the voice signal since clipping produces a higher than expected incidence of first discrete derivatives having a value of zero, or nearly zero.